Use of Hybrid Algorithm for Surface Roughness Optimization in Ti-6Al-4V Machining

  • Grynal D’Mello
  • P. Srinivasa Pai
  • Adarsh Rai
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 801)


In this study, an effort has been made to develop a hybrid optimization algorithm based on Particle Swarm Optimization (PSO), a widely used optimization technique and Bat Algorithm (BA) a newly introduced metaheuristic algorithm. The machining parameters namely cutting speed (V c ), feed rate (f), depth of cut (d) along with tool wear (VB) and cutting tool vibrations (V y ) are the inputs. Further a Hybrid PSO-BA algorithm has been implemented in order to optimize surface roughness in High Speed Turning (HST) of Ti-6Al-4V. It was observed that the proposed hybrid PSO-BA algorithm increases the accuracy and convergence by 1.92% and 4.17% for R a and R t , which are surface roughness parameters compared to BA. Validation experiments have been performed based on PSO-BA predicted values. The experimental values are close to the predictive values with an error of 0.47% for R a and 1.159% for R t which is considerably better than that obtained from BA only.


Ti-6Al-4V Surface roughness PSO BA Hybrid PSO-BA 



The authors grateful to AICTE, New Delhi, Ref. No.: 20/AICTE/RIFD/RPS(POLICY-1)/2012-13 for sponsoring this work under Research Promotion Scheme (RPS).


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.NMAM Institute of Technology, NitteKarkala Taluk, Udupi DistrictIndia

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